US 2011/0251493 A1 discloses a method for measuring physiological parameters comprising:                capturing a sequence of images of a human face;        identifying location of the face in a frame of the captured images and establishing a region of interest including the face;        separating pixels in the region of interest in a frame into at least two channel values forming raw traces over time;        decomposing the raw traces into at least two independent source signals; and        processing at least one of the source signals to obtain a physiological parameter.        
The document further discloses several refinements of the method. In particular, the use of remote photoplethysmographic (PPG) analyses is envisaged. Photoplethysmography is a commonly known optical measurement approach which can be used to detect blood volume changes in the microvascular bed of tissue of a monitored subject. Conventional PPG approaches include so-called contact PPG. Contact PPG requires measurement components (e.g., light sources and photodetectors) which basically have to be attached to a subject's skin. Consequently, standard photoplethysmography comprises obtrusive measurements, e.g. via a transceiver unit being fixed to the subject's earlobe or fingertip. Therefore, remote PPG measurement is often experienced as being unpleasant.
Typically, a standard (or: contact) PPG device includes artificial light sources to be directly attached to an indicative surface, e.g., a skin portion, of the subject to be observed. In this manner, avoidance or reduction of adverse effects is achieved. For instance, potentially disturbing incident radiation caused by other (or: ambient) light sources and undesired object motion with respect to the light source can be addressed. Correspondingly, also the receiver or detector, e.g. at least one photodiode, is closely fixed to the subject's skin patch of interest. In case the transceiver unit is too firmly fixed to the subject so as to avoid subject movement with respect to the equipment, signal quality can be deteriorated as well, e.g. due to undesired tissue compression.
Recently, remote PPG approaches applying unobtrusive measurements have been introduced. Basically, remote photoplethysmography utilizes light sources or, in general, radiation sources, disposed remote from the subject of interest. Preferably, for some applications, even readily available existing (ambient) light sources rather than defined special-purpose light sources are utilized. For instance, artificial light sources and/or natural light sources can be exploited. Consequently, in remote PPG environments, it has to be expected that due to widely changing illumination conditions, the detected signals generally provide a very small signal-to-noise ratio. Similarly, also a detector, e.g., a camera, can be disposed remote from the subject of interest for remote PPG measurements. Therefore, remote photoplethysmographic systems and devices are considered unobtrusive and can be adapted and well suited for everyday applications. The field of application may comprise unobtrusive inpatient and outpatient monitoring and even leisure and fitness applications. In this regard, it is considered beneficial that observed subjects can enjoy a certain degree of freedom of movement during remote PPG measurement.
Consequently, compared with standard (obtrusive) photoplethysmography, remote (unobtrusive) photoplethysmography is far more susceptible to distortion and noise. Undesired subject motion with respect to the detector and/or the radiation source can excessively influence signal detection. In particular, remote photoplethysmographic devices are frequently subjected to varying overall illumination conditions. Therefore, it has to be expected that the detected signals are almost always corrupted by noise and distortion.
In addition, remote photoplethysmography measurements may suffer from so-called specular reflections in the region of interest comprising at least a portion of the subject's skin tissue. Basically, specular reflection is considered a “mirror-like” reflection of incident radiation at a surface. Specular reflections may also occur at the skin surface of a living being. This applies in particular to greasy skin portions and, generally, to subjects having considerably dark skin (high content of melanin) Since skin portions which are subjected to specular reflections basically mirror incident radiation at the skin's surface to some extend, the reflected radiation contains only a part that results from penetrating the skin tissue. Therefore, radiation with specularly reflected parts is considered not directly indicative of the desired vital signals.
In summary, remote PPG is still considered to pose major challenges to signal detection and signal processing. Since the recorded data, such as captured reflected or emitted electromagnetic radiation (e.g., recorded image frames), always comprises, besides the desired signal to be extracted therefrom, further signal components deriving from overall disturbances, for instance noise due to changing luminance conditions (including specular reflections) and relative movement between the observed subject and the detection sensor, a detailed precise extraction of the desired signals is still considered to pose major problems for existing detection approaches and processing algorithms.
As a remedy, US 2011/0251493 A1 suggests to process the derived channel data, which correspond for example to each wavelength channel provided by an RGB image detection arrangement, through an Independent Component Analysis (ICA) by which separate signal components result. In the disclosed example, these are three signal components. One of these signal components comprises the desired information related to the vital signs to be detected, for example. However, the outcome which of the signal components contains the desired information may change from case to case. In order to choose the right signal component, it is suggested to identify the signal component with a periodic signal characteristic. This is further analyzed by transforming the time-dependent signal component into the frequency domain for analyzing the power spectrum.
Aside from being demanding with respect to computational resources, the presented method further needs significant signal length of up to one minute in order to being able to achieve a useful identification of the correct signal component by this transformation into the frequency domain. Furthermore, the presented method relies upon the assumption that the only periodic signal components after performing the ICA is the desired signal component containing the vital sign data. However, situations are possible where, for example, the aforementioned specular reflection may also result in a periodic signal component. This may be the case, by way of example, in an application where the subject that is to be monitored moves in a periodic way, for example, on an exercise device in a gym. In such an exemplary set-up, the presented method has difficulties of choosing the correct signal component after ICA and will provide erroneous vital sign data.